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Interpretable Fashion Matching with Rich Attributes., , , , , , and . SIGIR, page 775-784. ACM, (2019)Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure., , , and . CoRR, (2019)Cross-GCN: Enhancing Graph Convolutional Network with $k$k-Order Feature Interactions., , , and . IEEE Trans. Knowl. Data Eng., 35 (1): 225-236 (2023)Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure., , , and . IEEE Trans. Knowl. Data Eng., 33 (6): 2493-2504 (2021)Re4: Learning to Re-contrast, Re-attend, Re-construct for Multi-interest Recommendation., , , , , , , and . WWW, page 2216-2226. ACM, (2022)Accepted Tutorials at The Web Conference 2022., , , , , , , , , and 63 other author(s). WWW (Companion Volume), page 391-399. ACM, (2022)SoarGraph: Numerical Reasoning over Financial Table-Text Data via Semantic-Oriented Hierarchical Graphs., , , , , and . WWW (Companion Volume), page 1236-1244. ACM, (2023)On the Theories Behind Hard Negative Sampling for Recommendation., , , , , , and . WWW, page 812-822. ACM, (2023)MaSS: Model-agnostic, Semantic and Stealthy Data Poisoning Attack on Knowledge Graph Embedding., , , , , , and . WWW, page 2000-2010. ACM, (2023)SLED: Structure Learning based Denoising for Recommendation., , , , , , , , , and 1 other author(s). ACM Trans. Inf. Syst., 42 (2): 43:1-43:31 (March 2024)